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Mokalla TR and Mendu VVR

India is the second largest populated country in the world. The country accounts for nearly a third of the global burden
of stunting. Over 38%, or 46.6 million, children are stunted in India. While there are 51 million wasted children in the
world, India alone houses 25 million (50%) of them. In 45% of under-five child mortalities, chronic malnutrition is the
underlying factor (UNICEF, 2019). The term malnutrition comprises both undernutrition and overnutrition, and it is a
significant factor causing child mortality around the world (Markos, 2014). Stunting, wasting, and underweight are three
widely recognized indicators of a child’s physical growth and to describe the nutritional status (Khan, Zaheer and Safdar,
2019; Akombi, Agho, Merom, et al., 2017). According to National Family Health Survey (NFHS-4), the percentage
of children stunted, underweight, and wasting is 38%, 36%, and 21%, respectively, whose children aged 0-59 months
(International Institute for Population Studies [IIPS], 2017).
Literature also indicates significant variations in specific risk factors for child malnutrition through the application of
statistical models and several techniques (Kumar, Kumari and Singh, 2015; Messelu and Trueha, 2016; Mishra, Pandey,
Chaubey, et al., 2015; Corsi, Mejía-Guevara and Subramanian, 2015; Talukder, 2017; Boah, Azupogo, Amporfro et al.,
2019; Kang and Kim, 2019; Alom, Amirul and Quddus, 2009). We have employed multiple logistic regression model(s)

with binary outcomes and concentration index (CI) functions to examine the various determinants of under-nutrition and
its associated risk factors in India using NFHS-4 data.
The three leading indices are used to measure the nutritional imbalance resulting in child undernutrition. Stunting
(Short height for age) – is the reason for long-term nutritional inadequacy, which brings about reduced intellectual capacity,
poor school execution, and delayed mental development. The results in exposure of a child to repetitive infections or
diseases pose a higher risk for sickness and death, and it influences on financial productivity. In women, stunting leads
to numerous obstetric intricacies as a result of a smaller pelvis. It makes them give birth to newborn children with
low birth weights, and it causes infant growth which lean toward the shorter physical frame as adults (World Health
Organization [WHO], 2010). Wasting (low weight for length/height) – is a symptom of acute undernutrition, which
impairs the functions of the immune system. It exposes the child to infectious disease and an increased risk of death,
which is also a result of insufficient food consumption or a high frequency of irresistible illnesses, particularly diarrhea
(WHO, 2010). Underweight (low weight for age) – is a composite indicator of stunting and wasting, which is considered
both acute and chronic malnutrition (Mishra, Pandey, Chaubey, et al, 2015). Literature has demonstrated that the mortality
risk of underweight children increased (WHO, 2010)
According to the literature, child undernutrition was strongly associated with socioeconomic status such as mother’s
household status, education, and nutritional status, and demographic variables such as child age, birth duration, and child
size at birth (Messelu and Trueha, 2016; Corsi, Mejía-Guevara and Subramanian, 2015; Talukder, 2017; Boah, Azupogo,
Amporfro, et al., 2019; Kang and Kim, 2019; Alom, Amirul and Quddus, 2009; Dessie, Fentie, Abebe, et al., 2019;
Mishra, Pandey, Chaubey, et al., 2015; Kumar, Kumari and Singh., 2015).
The present study aims to investigate the socio-economic, demographic, and health determinants associated with
undernutrition among the under-five age of children from NFHS-4 data in India.
Therefore, the national level recent data (NFHS-4) of India are useful in understanding its causes, and to identify
the determinants of undernutrition among the under-five age of children. We hope that these findings will be helpful for
policymakers, researchers, and other stakeholders to formulate appropriate strategies for removing regional imbalance in
terms of undernutrition in the nation and its differential attributes among Indian states.

2. Data and Methods

Data are used from a 4 round of the NFHS-4, conducted by 2015-2016 (IIPS, 2017). The survey was conducted and
th
obtained information about population, nutrition, and health information from each of the 29 states, for each of the seven
union territories, of the total 640 districts in the country in India. The NFHS-4 was conducted by interviewing randomly
selected women aged 15-49 and men aged 15-54. Stratified 2-stage sampling was used as the sampling design for the
NFHS-4 study. In the first stage, the primary sampling units were selected, and in the second stage, the households for the
study were selected. Primary sampling units with at least 300 households were divided into segments of approximately
100-150 households. Two of the segments were selected using systematic sampling with probability proportional to size.
From each selected rural and urban cluster, 22 households were selected using systematic sampling. A total of 628,900
households were selected for the sample, of which 616,346 were occupied. Of the occupied households, 601,509 were
successfully interviewed, for a response rate of 9%. In the interviewed households, 723,875 eligible women age 15-49
were identified for individual women’s interviews. Interviews were completed with 699,686 women, for a response rate
of 97%. NFHS-4 first provided district-level estimates for several significant markers. For this study, we considered

International Journal of Population Studies | 2019, Volume 5, Issue 2 15